This proposal represent a request for continued support of our ongoing project exploring protein-ligand interactions and the thermodynamics of ligand binding to biological receptors. The overall objectives are aimed at developing and applying methods of free energy simulations to ligand binding thermodynamics, docking and protein-ligand interaction modeling. Specific efforts are directed to the development of a hierarchy of methods that provide suitable tools for high-throughput screening, as well as detailed ligand refinement techniques employing accurate atomic force fields and adequate sampling. In addition, ligand-binding landscapes will be constructed as a function of several coordinates that decribe the progress in binding for protein-ligand pairs, such as benzamidine-tryspin (millimolar) and biotin-streptavidin (femptomolar), using detailed atomic force fields with explicit, as well as implicit solvent models. The nature and control of landscape roughness will provide key insights into efficient docking algorithms, as well as ligand-binding kinetics. Complementing these "first principles," investigations will be continued on the development of the Ligand-Protein DataBase (LPDB, http:/Ipdb.scripps.edu) for the evaluation and assessment of current methods and force fields for ligand docking, binding assessments and ranking. We will continue to refine and add to this publicly accessible database, as well as use it to examine exisiting and new energy (scoring) functions for ligand-protein binding studies. Additionally, we will explore the ability of "physics-based" force fields to do the same, including those that implement solvation via implicit schemes such as GB/SA or PB/SA. To augment these studies, we will develop and examine new grid-based docking methods that build upon the genetic algorithm and Monte Carlo/simulated annealing approaches established in the past. A final focus will be the continuing development of our extended system methods for chemical free energy perturbation calculations, lambda-dynamics. We plan to use lambda-dynamics to explore the optimization problem associated with maintaining an acceptable level of inhibition by a given compound when faced with multiple "environments"; i.e., receptors, while, at the same time, keeping the binding of substrates to these receptors relatively high. The lambda-dynamics approach will be extended to consider a number of possible scenarios aimed at elucidating questions about ligand design in the presence of bioligoically imposed constraints and resistance "pathways". [unreadable] [unreadable]